Now that all of our existing sheep are in LambTracker and the 2014 lambs’ data is only in LambTracker I started seriously working to enter in the 16 year history of the flock into the database. I’ve discovered a number of issues and developed some workflows that seem to be making the process go much faster. This post will be updated a bit as I get everything documented.

I started LambTracker with the assumption that you would not have to enter in all the history before you started using it. This is good for allowing the users to test the viability of the software first but does make adding reams of back data more painful. Here is the current workflow I am using as I enter in 16 years of history with our flock.

1. Pick a table within the LambTracker database to work on.
2. If the table already has data in it then do a query to get all the data out and save it as a .csv file. If you do not have any data in that table now the get a copy of the blank spreadsheet document that replicates the structure of that table.

Now you have to take one of 2 paths depending on whether you are updating existing records or inserting new ones.

For updating the existing table and its data:

Bring the .csv file into a spreadsheet program. I use LibreOffice. Take care to ensure that fields that might appear to be numbers (NSIP ID, registration ID and so on) are brought in as text fields only.

Edit the spreadsheet file to update and add missing information as required.

Save a copy as a .csv file.

Use a csv to sql tool to create update statements for the file.

Back up your existing LambTracker database.

Run the queries to update the database.

Verify the new data are in correctly.

Back up the database again.

Repeat as necessary for each table to update.

For inserting new records into the table:

Edit a copy of the blank spreadsheet document that replicates the structure of that table adding data as required. Pay particular attention to the format and ensure that all text fields are really stored as text. Also dates must be in the format YYYY-MM-DD stored as text for LambTracker to work properly. Times are stored as text fields too HH:MM:SS

Save a copy as a .csv file.

Use a csv to sql tool to create update statements for the file.

Back up your existing LambTracker database.

Run the queries to insert new records into the database.

Verify the new data are in correctly.

Back up the database again.

Repeat as necessary for each table to create or add to.

There is a lot more that I’ve discovered about how to do this efficiently but this is the gist of it.

Been going round and round on several options for the LambTracker Desktop app.

Initial choices, Swing or Java FX. I had about settled on Swing because I really don’t want to keep supporting Oracle. Then Cards or not as a structure. Was still waffling back and forth and then this:

Run Android Apps in Chrome Browser

APK Packager

Started following the details, the required SW is now on the Google Play Store so it’s more official with every passing minute.

A quick test showed that on Linux machines LambTracker runs. The only issue is trying to figure out where the virtual SD card is. I need to know so I can backup and work with the database. I didn’t’ get it running on my Mac yet but I haven’t really had time to play with it much either.

Anyway, I’m attempting to get the existing LambTracker application running on my Mac and do some further testing.

One option is to write an Android Activity that is the desktop side assuming that this will continue as an option and go from there. One advantage, it buys us cross platform capability right away.

Still pondering but this looks promising.

We are about to start our major sheep evaluation cycle. I’ve added most of the NSIP EBV data points into the database and al writing the queries to display the data along with the most recent evaluation. Alex has found several bugs that we never see here and fixed them for which I am grateful. Bug fixes and some needed new features are being implemented but things are taking longer to do as fall farm work is ramping up. Hoping to get the re-vamped evaluate sheep module finished by the middle of October.